1. Field of the Invention
The present invention relates to a wireless communication apparatus, a wireless communication method, a computer program, and a wireless communication system, and more particularly, to a wireless communication apparatus, a wireless communication method, a computer program, and a wireless communication system performing communication using a MIMO (multiple input multiple output) scheme.
2. Description of the Related Art
A wireless communication system has been proposed in which a transmitter and a receiver each have a plurality of antennas and space division multiplexing communication (MIMO scheme: multiple input multiple output) is performed using the plurality of antennas to increase transmission capacity.
FIG. 17 is a conceptual diagram illustrating a wireless communication system using the MIMO scheme. In a wireless communication system 1 shown in FIG. 17, a transmitter 11 includes M antennas 12a, 12b, . . . , 12m, and a receiver 21 includes N antennas 22a, 22b, . . . , 22n. 
The transmitter 11 performs space/time division multiplexing on K transmission data, distributes the data to M antennas 12a, 12b, . . . , 12m, and transmits the data through channels. Then, the receiver 21 receives the signals transmitted through the channels using N antennas 22a, 22b, 22n, and performs space/time division demultiplexing on the received signals to obtain K reception data.
Therefore, the MIMO scheme is a communication system using channel characteristics in which the transmitter 11 distributes transmission data to a plurality of antennas and transmits it through the antennas, and the receiver 21 receives signals using a plurality of antennas and processes the signals to obtain reception data.
There are various data transmission systems using the MIMO scheme. As an ideal example of the data transmission system using the MIMO scheme, an eigenmode transmission system has been known which uses the singular value decomposition (SVD) or the eigenvalue decomposition of a channel matrix.
FIG. 18 is a conceptual diagram illustrating the eigenmode transmission system. In the eigenmode transmission system using SVD, singular value decomposition is performed on a channel matrix H having channel information between transmitting and receiving antennas as elements to calculate UDVH (VH indicates a complex conjugate transposed matrix of a matrix V). Singular value decomposition is performed on the channel matrix H to calculate UDVH, the matrix V is given as a transmitter-side antenna weighting coefficient matrix, and a matrix UH (UH indicates a complex conjugate transposed matrix of a matrix U) is given as a receiver-side antenna weighting coefficient matrix. In this way, a channel can be represented by a diagonal matrix D having the square root (singular value) of an eigenvalue λi of a covariance matrix (HHH or HHH) of the channel matrix H. Therefore, it is possible to multiplex a signal and transmit the multiplexed signal, without any crosstalk.
When the number of antennas of the transmitter 11 is M, a transmission signal x′ is represented by an M×1 vector. When the number of antennas of the receiver 21 is N, a received signal y′ is represented by an N×1 vector. In addition, a channel matrix is represented as a matrix H of N rows and M columns. An element hij of the channel matrix H is a transfer function from a j-th transmitting antenna to an i-th receiving antenna (1≦i≦N and 1≦j≦M). The received signal vector y′ is obtained by adding a noise vector n to the multiplication of the channel matrix H and the transmission signal vector x′, as represented by the following Expression 1.y′=Hx′+n  (Expression 1)
As described above, when singular value decomposition is performed on the channel matrix H, the following Expression 2 is obtained.H=UDVH  (Expression 2)
The transmitter-side antenna weighting coefficient matrix V and the receiver-side antenna weighting coefficient matrix UH are unitary matrices that satisfy the following Expressions 3 and 4. In the following Expressions, I indicates a unitary matrix.UHU=I  (Expression 3)VHV=I  (Expression 4)
That is, the antenna weighting coefficient matrix UH of the receiver 21 is obtained by arranging the normalized eigenvectors of HHH, and the antenna weighting coefficient matrix V of the transmitter 11 is obtained by arranging the normalized eigenvectors of HHH. In addition, D indicates a diagonal matrix having the square root of (the singular value of H) of the eigenvalue of HHH or HHH as a diagonal component. That is, when the smaller one of the number M of transmitting antennas of the transmitter 11 and the number N of receiving antennas of the receiver 21 is referred to as L (=min(M, N)), the matrix D is a square matrix of L rows and L columns. That is, the matrix D can be represented by the following Expression 5.
                    D        =                  (                                                                                          λ                    1                                                                              0                                            …                                            0                                                                    0                                                                                  λ                    2                                                                              …                                            0                                                                    ⋮                                            ⋮                                            ⋱                                            ⋮                                                                    0                                            0                                            …                                                                                  λ                    L                                                                                )                                    (                  Expression          ⁢                                          ⁢          5                )            
When the transmitter 11 multiplies data by the antenna weighting coefficient matrix V and transmits the data and the receiver 21 receives a signal and multiplies the signal by the complex conjugate transposed matrix UH, the received signal y is represented by the following Expression 6 since the matrix U of N rows and L columns and the matrix V of M rows and L columns are unitary matrices.y=UHy′=UH(Hx′+n)=UH(HVx+n)=UH(UDVH)Vx+UHn =(UHU)D(VHV)x+UHn =IDIx+UHn =Dx+UHn  (Expression 6)
In this case, each of the received signal y and the transmission signal x is a vector of L rows and one column. Since the matrix D is a diagonal matrix, each transmission signal transmitted from the transmitter 11 can be received by the receiver 21 without any crosstalk. Since the diagonal element of the matrix D is the square sum of the eigenvalue λi (1≦i≦L), the power of each reception signal is λi times the power of each transmission signal. In addition, for the noise component n, since the column of U is an eigenvector having a norm that is normalized to 1, UHn does not change the noise power thereof. Therefore, UHn is a vector of L rows and one column, and the received signal y and the transmission signal x have the same size.
As such, in the eigenmode transmission system using the MIMO scheme, it is possible to obtain a plurality of independent logic pulses having the same frequency at the same time without any crosstalk. That is, it is possible to wirelessly transmit a plurality of data using the same frequency at the same time, thereby improving a transmission rate.